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Verification and Validation of the PLTEMP/ANL Code for Thermal-Hydraulic Analysis of Experimental and Test Reactors, Volume 1

This is Volume 1 of a two-volume document that collects the verification and validation (V&V) works done for the PLTEMP/ANL code during the years of its development and improvement. Volume 1 describes the V&V of sixteen capabilities of the PLTEMP/ANL code that were identified by research reactor analysts as frequently used in their thermal-hydraulic analysis. Volume 2 describes the V&V of developments and improvements since the release of PLTEMP/ANL Version 4.3. Each chapter of the document focuses on verifying or validating a specific part of the software that calculates a specific phenomenon, e.g., channel flow calculation, coolant property calculation, heat transfer calculation, and flow instability calculation. Software verification is performed by comparing the code with hand calculation, Microsoft spreadsheet calculation, Mathematica calculation, or MATLAB calculation. The software validation is done by comparing the code with experimental data or a widely tested code like the RELAP5 code. In addition, some PLTEMP/ANL V&V works that are available in the open literature are simply cited in Volume 1 of the document. PLTEMP/ANL has been used in the safety analysis reports of several US and foreign research reactors licensed and converted from highly enriched uranium fuel to low-enriched uranium fuel. A list of such reactors is given in Volume 1 of the document.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Metagenomics Reveals Diet-Specific Specialization of Bacterial Communities in Fungus Gardens of Grass- and Dicot-Cutter Ants

Leaf-cutter ants in the genus Atta are dominant herbivores in the Neotropics. While most species of Atta cut dicots to incorporate into their fungus gardens, some species specialize on grasses. Here we examine the bacterial community associated with the fungus gardens of grass- and dicot-cutter ants to examine how changes in substrate input affect the bacterial community. We sequenced the metagenomes of 12 Atta fungus gardens, across four species of ants, with a total of 5.316 Gbp of sequence data. We show significant differences in the fungus garden bacterial community composition between dicot- and grass-cutter ants, with grass-cutter ants having lower diversity. Reflecting this difference in community composition, the bacterial functional profiles between the fungus gardens are significantly different. Specifically, grass-cutter ant fungus garden metagenomes are particularly enriched for genes responsible for amino acid, siderophore, and terpenoid biosynthesis while dicot-cutter ant fungus gardens metagenomes are enriched in genes involved in membrane transport. Differences between community composition and functional capacity of the bacteria in the two types of fungus gardens reflect differences in the substrates that the ants incorporated. These results show that different substrate inputs matter for fungus garden bacteria and shed light on the potential role of bacteria in mediating the ants’ transition to the use of a novel substrate.

59 BASIC BIOLOGICAL SCIENCES↗

In vitro prototyping and rapid optimization of biosynthetic enzymes for cell design

The design and optimization of biosynthetic pathways for industrially relevant, non-model organisms is challenging due to transformation idiosyncrasies, reduced numbers of validated genetic parts and a lack of high-throughput workflows. Here we describe a platform for in vitro prototyping and rapid optimization of biosynthetic enzymes (iPROBE) to accelerate this process. In iPROBE, cell lysates are enriched with biosynthetic enzymes by cell-free protein synthesis and then metabolic pathways are assembled in a mix-and-match fashion to assess pathway performance. We demonstrate iPROBE by screening 54 different cell-free pathways for 3-hydroxybutyrate production and optimizing a six-step butanol pathway across 205 permutations using data-driven design. Observing a strong correlation (r = 0.79) between cell-free and cellular performance, we then scaled up our highest-performing pathway, which improved in vivo 3-HB production in Clostridium by 20-fold to 14.63 ± 0.48 g l -1 . Finally, we expect iPROBE to accelerate design–build–test cycles for industrial biotechnology.

36 MATERIALS SCIENCE↗

Dissolution of Mg-enriched defects in implanted GaN and increased p-type dopant activation

Annealing Mg-implanted homoepitaxial GaN at temperatures above 1400 °C eliminates the formation of inversion domains and leads to improved dopant activation efficiency. Extended defects, in the form of inversion domains, contain electrically inactive Mg after post-implantation annealing at temperatures as high as 1300 °C (one GPa N 2 overpressure), which results in a low dopant activation efficiency. Triple-axis x-ray data reveal that implant-induced strain is fully relieved after annealing at 1300 °C for 10 min, indicating that strain-inducing point defects formed during implantation have reconfigured and inversion domains are formed. However, annealing at temperatures of 1400–1500 °C (one GPa N 2 overpressure) eliminates the presence of the inversion domains. While residual defects, such as dislocation loops, still exist after annealing at and above 1400 °C, chemical analysis at multiple dislocation loops shows no sign of Mg segregation. Meanwhile, an overall decreasing trend in the dislocation loop density is observed after annealing at the higher temperatures and longer times. Additionally, once inversion domains are formed and the samples are cooled to room temperature, they are shown to dissolve with subsequent annealing above 1400 °C. While such defects have been observed before, the important finding that such defects can be dissolved with a short, higher temperature step is key. Earlier work [Breckenridge et al., J. Appl. Phys. Lett. 118, 022101 (2021)] addressing electrical measurements of these types of samples showed that annealing at 1400 °C leads to a dopant activation efficiency that is an order of magnitude higher than that observed at 1300 °C. In conclusion, this work complements earlier work by identifying the inversion domains, which incorporate Mg, and points to the benefits, in terms of defect density and p-type dopant activation, of using higher temperature (>1400 °C) annealing cycles to activate Mg in GaN, even if the Mg-containing inversion domains had been formed during lower temperature annealing.

36 MATERIALS SCIENCE↗

The Bear Brook Watershed in Maine: Multi-Decadal Whole-Watershed Experimental Acidification

The Bear Brook Watershed in Maine (BBWM) is a long-term research site established to study the response of forest ecosystem function to environmental disturbances of chronic acidic deposition and ecosystem nitrogen enrichment. Starting in 1989, the West Bear (treated) watershed received bimonthly applications of ammonium sulfate [(NH4)2SO4] fertilizer from above the canopy, whereas East Bear (reference) received ambient deposition. The treatments were stopped in 2016, marking the beginning of the recovery phase. Research at the site has focused on soils, streams, and vegetation. Here, we describe data collected over three decades at the BBWM—input and stream output nutrient fluxes, quantitative soil pits and soil chemistry, and soil temperature and moisture.

Patel, Kaizad F.↗

Proteomic Profiling of the Substantia Nigra to Identify Determinants of Lewy Body Pathology and Dopaminergic Neuronal Loss

Proteinaceous aggregates containing ?-synuclein protein called Lewy bodies in the substantia nigra is a hallmark of Parkinson’s disease. The molecular mechanisms of Lewy body formation and associated neuronal loss remain largely unknown. To gain insights on proteins and pathways associated with Lewy body pathology, we performed quantitative profiling of the proteome. We analyzed substantia nigra tissue from 51 subjects arranged into three groups: cases with Lewy body pathology, Lewy body-negative controls with matching neuronal loss and controls with no neuronal loss. Using label-free LC-MS/MS approach we quantified the 2,963 most abundant proteins. Statistical testing for differential protein abundance, followed by pathway enrichment and Bayesian learning of the causal network structure were performed to identify likely drivers of Lewy body formation and dopaminergic neuronal loss. The identified pathways include (1) Arp2/3 complex-mediated actin nucleation; (2) synaptic function; (3) poly(A) RNA binding; (4) basement membrane and endothelium; and (5) hydrogen peroxide metabolic process. According to the data, the endothelial/basement membrane pathway is tightly connected with both pathologies and likely to be one of the drivers of the neuronal loss. The poly(A) RNA-binding proteins, including the ones relevant to other neurodegenerative disorders (e.g. TDP-43 and FUS) have strong inverse correlation with Lewy bodies and may reflect alternative mechanism of nigral neurodegeneration.

Petyuk, Vladislav A.↗

Engineered Accumulation of Protocatechuate in Corn Biomass to Enhance Biomanufacturing

The in-planta accumulation of coproducts in crops can enhance the value of lignocellulosic biomass and facilitate a sustainable bioeconomy. Corn stover represents a major renewable source of lignocellulose for the production of advanced biofuels and bioproducts. In this study, we engineered corn with a bacterial gene encoding a dehydroshikimate dehydratase (QsuB) to overproduce protocatechuate (DHBA). Transgenic corn lines accumulate up to 2.9% DHBA on a dry weight basis in leaf and stem biomass. DHBA occurs in the form of glucosides that are extractable from biomass using aqueous methanol as the solvent. The analysis of lignin did not show any evidence for the incorporation of DHBA; however, an increase in the lignin syringyl to guaiacyl ratio and a higher relative abundance of p-coumarate groups compared with total lignin units were observed in QsuB-modified corn. Alkaline hydrolysates prepared from QsuB corn were enriched in DHBA compared to the hydrolysates obtained from wild-type biomass, which contained mostly p-coumarate and ferulate. Using engineered Novosphingobium aromaticivorans as a production host, a 375% improvement in 2-pyrone-4,6-dicarboxylate titers was achieved through biological upgrading of alkaline hydrolysates derived from QsuB corn compared to unmodified biomass. Our data demonstrate an engineering strategy to overproduce DHBA in corn that can facilitate sustainable manufacturing of other valuable bioproducts using stover as a feedstock.

2-pyrone-4,6-dicarboxylate↗

Predictive models of the genetic bases underlying budding yeast fitness in multiple environments

Abstract The ability of organisms to adapt and survive depends on the effects of genes and the environment on fitness. However, the multigenic nature of fitness and genotype-by-environment interactions hinder our understanding of the genetic basis of fitness. Here, we established fitness prediction models for 35 environments using machine learning and existing fitness data and different genetic variant types for a Saccharomyces cerevisiae population. Models revealed that the predictive ability of genetic variants varied across environments, with copy number variants explaining the majority of fitness variation in most cases. Model interpretation showed that different variant types identified distinct gene sets associated with predictive variants. These gene sets were significantly enriched in experimentally validated genes affecting fitness in only a subset of environments, indicating that many genes influencing fitness remain unexplored. Notably, non-experimentally validated genes were more important than validated ones for fitness predictions. Gene contributions to predictions were both isolate- and environment-dependent, pointing to gene-by-gene and gene-by-environment interactions. Furthermore, models uncovered experimentally validated and novel candidate genetic interactions for a well-characterized stress, the fungicide benomyl. These findings highlight the feasibility of identifying the genetic basis of fitness by using different genetic variant types and offer novel targets for future functional analysis.

DNA copy number variations↗

R-matrix Resolved Resonance Region Evaluation of 140,142 Ce

Oak Ridge National Laboratory completed the resolved resonance region (RRR) evaluation of the two most abundant cerium isotopes, 140 Ce (88.45%) and 142 Ce (11.11%), as requested by the US Nuclear Criticality Safety Program. These evaluations are based on recent high-resolution transmission and capture measurements performed on nat Ce and highly enriched 142 Ce samples at the JRC-Geel Linear Accelerator facility, as well as measured thermal constants available from the EXFOR database. Starting from the resonance parameters of the ENDF/B-VIII.0 library followed by a preliminary R-matrix analysis, an updated set of resonance parameters and corresponding covariance information were derived by fitting these measured data using the Reich–Moore approximation of the R -matrix theory, as implemented in the SAMMY code system. The 140 Ce RRR upper energy limit was kept at 200 keV, whereas the 142 Ce resonance region was extended from 13 to 26 keV. Updated statistical properties were obtained for the new evaluations and compared to those derived from the ENDF/B-VIII.0 nuclear data library. The new evaluation work improved some of the discrepancies found in previous work, such as the capture resonance integral and stellar Maxwellian-averaged cross sections. These integral quantities were mainly derived from the fit of the latest measured data, especially the neutron capture yield data for 142 Ce isotope.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Applying Physics-Informed Neural Networks to Solve Navier–Stokes Equations for Laminar Flow around a Particle

In recent years, Physics-Informed Neural Networks (PINNs) have drawn great interest among researchers as a tool to solve computational physics problems. Unlike conventional neural networks, which are black-box models that “blindly” establish a correlation between input and output variables using a large quantity of labeled data, PINNs directly embed physical laws (primarily partial differential equations) within the loss function of neural networks. By minimizing the loss function, this approach allows the output variables to automatically satisfy physical equations without the need for labeled data. The Navier–Stokes equation is one of the most classic governing equations in thermal fluid engineering. This study constructs a PINN to solve the Navier–Stokes equations for a 2D incompressible laminar flow problem. Flows passing around a 2D circular particle are chosen as the benchmark case, and an elliptical particle is also examined to enrich the research. The velocity and pressure fields are predicted by the PINNs, and the results are compared with those derived from Computational Fluid Dynamics (CFD). Additionally, the particle drag force coefficient is calculated to quantify the discrepancy in the results of the PINNs as compared to CFD outcomes. The drag coefficient maintained an error within 10% across all test scenarios.

Hu, Beichao (ORCID:0009000163215151)↗

Infrared spectroscopic method for uranium isotopic analysis

A high performance infrared (HPIR) system was developed and demonstrated for the infrared absorption analysis of {sup 235}U and {sup 238}U isotopes in uranium hexafluoride gas samples. Sweeping the quantum cascade laser light source over the spectral range and sampling via a high-rate analog-to-digital converter provided 0.0005 cm-1 spectral resolution, which allowed for high-precision measurements of the isotopic peak shift. A data analysis method was developed using principal component analysis to predict the isotope weight % content of {sup 235}U. The HPIR precision, accuracy, and error were evaluated for a wide range of isotopic ratio samples (0.287 – 93.7 weight % {sup 235}U), and the results were compared to the International Target Values (ITVS) set forth by the International Atomic Energy Agency (IAEA) for non-destructive and destructive analytical techniques. The method meets or surpasses the IAEA ITVs for non-destructive analysis of samples with isotopic content of depleted to highly enriched. The results also demonstrated the capability of the HPIR system to correctly predict the {sup 235}U weight % content of a mislabeled sample whose isotopic distribution was validated by mass spectroscopic measurements. The HPIR measurement is nondestructive and, thus, allows for confirmatory analyses of the exact sample at a designated IAEA lab if higher-resolution or a certified analysis is needed. (author)

07 ISOTOPE AND RADIATION SOURCES↗

Learning high-dimensional parametric maps via reduced basis adaptive residual networks

We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs and outputs. When just few training data are available, it is beneficial to have a compact parametrization in order to ameliorate the ill-posedness of the neural network training problem. By linearly restricting high-dimensional maps to informed reduced bases of the inputs, one can compress high-dimensional maps in a constructive way that can be used to detect appropriate basis ranks, equipped with rigorous error estimates. A scalable neural network learning framework is thus to learn the nonlinear compressed reduced basis mapping. Unlike the reduced basis construction, however, neural network constructions are not guaranteed to reduce errors by adding representation power, making it difficult to achieve good practical performance. Inspired by recent approximation theory that connects ResNets to sequential minimizing flows, we present an adaptive ResNet construction algorithm. This algorithm allows for depth-wise enrichment of the neural network approximation, in a manner that can achieve good practical performance by first training a shallow network and then adapting. We prove universal approximation of the associated neural network class for $L^2_v$ functions on compact sets. Our overall framework allows for constructive means to detect appropriate breadth and depth, and related compact parametrizations of neural networks, significantly reducing the need for architectural hyperparameter tuning. Numerical experiments for parametric PDE problems and a 3D CFD wing design optimization parametric map demonstrate that the proposed methodology can achieve remarkably high accuracy for limited training data, and outperformed other neural network strategies we compared against.

42 ENGINEERING↗

Data for Coprocessing Corn Germ Meal for Oil Recovery and Ethanol Production, a Process Model for Lipid-Producing Energy Crops

Efforts to engineer high-productivity crops to accumulate oils in their vegetative tissue present the possibility of expanding biodiesel production. However, processing the new crops for lipid recovery and ethanol production from cell wall saccharides is challenging and expensive. In a previous study using corn germ meal as a model substrate, we reported that liquid hot water (LHW) pretreatment enriched the lipid concentration by 2.2 to 4.2 fold. This study investigated combining oil recovery with ethanol production by extracting oil following LHW and simultaneous saccharification and co-fermentation (SSCF) of the biomass. Corn germ meal was again used to model the oil-bearing energy crops. Pretreated germ meal hydrolysate or solids (160 °C and 180 °C for 10 minutes) were fermented, and lipids were extracted from both the spent fermentation whole broth and fermentation solids, which were recovered by centrifugation and convective drying. Lipid contents in spent fermentation solids increased 3.7 to 5.7 fold compared to the beginning germ meal. The highest lipid yield achieved after fermentation was 36.0 mg lipid g−1 raw biomass; the maximum relative amount of triacylglycerol (TAG) was 50.9% of extracted oil. Although the fermentation step increased the lipid concentration of the recovered solids, it did not improve the lipid yields of pretreated biomass and detrimentally affected oil compositions by increasing the relative concentrations of free fatty acids.

Conversion↗

Natural variation and improved genome annotation of the emerging biofuel crop field pennycress ( Thlaspi arvense )

The Brassicaceae family comprises more than 3,700 species with a diversity of phenotypic characteristics, including seed oil content and composition. Recently, the global interest in Thlaspi arvense L. (pennycress) has grown as the seed oil composition makes it a suitable source for biodiesel and aviation fuel production. However, many wild traits of this species need to be domesticated to make pennycress ideal for cultivation. Molecular breeding and engineering efforts require the availability of an accurate genome sequence of the species. Here, we describe pennycress genome annotation improvements, using a combination of long- and short-read transcriptome data obtained from RNA derived from embryos of 22 accessions, in addition to public genome and gene expression information. Our analysis identified 27,213 protein-coding genes, as well as on average 6,188 biallelic SNPs. In addition, we used the identified SNPs to evaluate the population structure of our accessions. The data from this analysis support that the accession Ames 32872, originally from Armenia, is highly divergent from the other accessions, while the accessions originating from Canada and the United States cluster together. When we evaluated the likely signatures of natural selection from alternative SNPs, we found 7 candidate genes under likely recent positive selection. These genes are enriched with functions related to amino acid metabolism and lipid biosynthesis and highlight possible future targets for crop improvement efforts in pennycress.

59 BASIC BIOLOGICAL SCIENCES↗

Cylindricity Sensitivity Thermal Model of the AGR-5/6/7 Experiment in the Advanced Test Reactor

The AGR-5/6/7 experiment is currently being irradiated in the Advanced Test Reactor (ATR) at the Idaho National Laboratory and is approximately 70% complete. Several fuel and material irradiation experiments have been planned for the U.S. Department of Energy Advanced Gas Reactor Fuel Development and Qualification Program, which supports the development and qualification of tristructural isotropic (TRISO) coated particle fuel for use in high-temperature gas-cooled reactors. The goals of these experiments are to provide irradiation performance data to support fuel process development, qualify fuel for normal operating conditions, support development of fuel performance models and codes, and provide irradiated fuel and materials for post-irradiation examination and safety testing. Originally planned and named as separate fuel experiments, but subsequently combined into a single test train, AGR-5/6/7 is testing low-enriched uranium oxycarbide TRISO fuel. The AGR-5/6/7 test train has 5 capsules with thermocouples and independent gas control mixtures. Unique to this paper is a sensitivity study concerning the cylindricity of the graphite holders containing the fuel compacts and their eccentricity in relation to the stainless-steel capsule walls. Each capsule has small nubs on the outside used for centering the graphite holder inside the stainless-steel capsule with a small gas gap used to control temperature. Due to machining tolerances of these nubs and vibration wearing the nubs down when the experiment is running in the reactor, the possibility exists that the holder may move around radially. Each capsule is equipped with several thermocouples placed at various radii and depths within each graphite holder. This paper will show the sensitivity of offsetting the graphite holder for various radii in 45-degree increments around the circle with the objective of minimizing the difference between the measured thermocouples and the modeled thermocouple temperatures. Separate gas mixtures of helium/neon are introduced into this gas gap between the holder and capsule wall and changed as necessary to maintain the desired thermocouple temperatures to keep the fuel compacts at constant temperature as the nuclear reactor conditions change. The goal of the sensitivity study is to find a radius and an angle to offset the holder from perfectly centered for each of the five capsules separately. The complex thermal model includes fission heating, gamma heating, radiation heat transfer, and heat transfer via conduction and radiation across the control gaps. Subroutines linked to the thermal model offer an easy method to offset the graphite holder from the capsule walls without remeshing the entire model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Design of Mini-Plate-1 Irradiation Test for Qualification of High-Density, Low-Enriched U-10Mo Monolithic Fuel

The United States High Performance Research Reactor project is tasked with fuel development and qualification leading to conversion of higher power research and test reactors in the US from high-enriched uranium (HEU) to low-enriched uranium (LEU) fuels. Here, this manuscript identifies the functional and operational design requirements of the first miniature test plate (mini-plate [MP]) irradiation campaign (MP-1) of commercially fabricated LEU U-10Mo monolithic plate-type fuel and is the precursor to a large parametric mini-plate test (MP-2) aimed at producing the data to support regulatory qualification of the LEU U-10Mo monolithic fuel. The manuscript (1) provides a general description of the selected U-10Mo LEU fuel and (2) defines the overall experiment design and functional requirements to accomplish the specific test objective of MP-1, which is to confirm that the commercially manufactured LEU U-10Mo monolithic fuel meets the established requirements of geometric stability, mechanical integrity and stable and predictable behavior. The fuel testing parameters are established by the need to bound performance behavior within the operational envelope of the reactors being converted.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Regulation of β-cell death by ADP-ribosylhydrolase ARH3 via lipid signaling in insulitis

Lipids are regulators of insulitis and β-cell death in type 1 diabetes development, but the underlying mechanisms are poorly understood. Here, we investigated how the islet lipid composition and downstream signaling regulate β-cell death. We performed lipidomics using three models of insulitis: human islets and EndoC-βH1 β cells treated with the pro-inflammatory cytokines interlukine-1β and interferon-γ, and islets from pre-diabetic non-obese mice. We also performed mass spectrometry and fluorescence imaging to determine the localization of lipids and enzyme in islets. RNAi, apoptotic assay, and qPCR were performed to determine the role of a specific factor in lipid-mediated cytokine signaling. Across all three models, lipidomic analyses showed a consistent increase of lysophosphatidylcholine species and phosphatidylcholines with polyunsaturated fatty acids and a reduction of triacylglycerol species. Imaging assays showed that phosphatidylcholines with polyunsaturated fatty acids and their hydrolyzing enzyme phospholipase PLA2G6 are enriched in islets. In downstream signaling, omega-3 fatty acids reduce cytokine-induced β-cell death by improving the expression of ADP-ribosylhydrolase ARH3. The mechanism involves omega-3 fatty acid-mediated reduction of the histone methylation polycomb complex PRC2 component Suz12, upregulating the expression of Arh3, which in turn decreases cell apoptosis. Our data provide insights into the change of lipidomics landscape in β cells during insulitis and identify a protective mechanism by omega-3 fatty acids.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of pleiotropic loci mediating structural and non-structural carbohydrate accumulation within the sorghum bioenergy association panel using high-throughput markers

Molecular characterization of diverse germplasm can contribute to breeding programs by increasing genetic gain for sorghum [ Sorghum bicolor (L.) Moench] improvement. Identifying novel marker-trait associations and candidate genes enriches the existing genomic resources and can improve bioenergy-related traits using genomic-assisted breeding. In the current scenario, identifying the genetic loci underlying biomass and carbon partitioning is vital for ongoing efforts to maximize each carbon sink’s yield for bioenergy production. Here, we have processed a high-density genomic marker (22 466 550) data based on whole-genome sequencing (WGS) using a set of 365 accessions from the bioenergy association panel (BAP), which includes ~19.7 million (19 744 726) single nucleotide polymorphism (SNPs) and 2.7 million (~2 721 824) insertion deletions (indels). A set of high-quality filtered SNP (~5.48 million) derived markers facilitated the assessment of population structure, genetic diversity, and genome-wide association studies (GWAS) for various traits related to biomass and its composition using the BAP. The phenotypic traits for GWAS included seed color (SC), plant height (PH), days to harvest (DTH), fresh weight (FW), dry weight (DW), brix content % (BRX), neutral detergent fiber (NDF), acid detergent fiber (ADF), non-fibrous carbohydrate (NFC), and lignin content. Several novel loci and candidate genes were identified for bioenergy-related traits, and some well-characterized genes for plant height ( Dw1 and Dw2 ) and the YELLOW SEED1 locus ( Y1 ) were validated. We further performed a multi-variate adaptive shrinkage analysis to identify pleiotropic QTL, which resulted in several shared marker-trait associations among bioenergy and compositional traits. Significant marker-trait associations with pleiotropic effects can be used to develop molecular markers for trait improvement using a marker-assisted breeding approach. Significant nucleotide diversity and heterozygosity were observed between photoperiod-sensitive and insensitive individuals of the panel. This diverse bioenergy panel with genomic resources will provide an excellent opportunity for further genetic studies, including selecting parental lines for superior hybrid development to improve biomass-related traits in sorghum.

bioenergy association panel↗